Tight upper bounds for the convergence of the randomized extended Kaczmarz and Gauss–Seidel algorithms
Author:
Affiliation:
1. Fujian Provincial Key Laboratory of Mathematical Modeling and High‐Performance Scientific Computing, School of Mathematical SciencesXiamen University Xiamen China
Funder
National Natural Science Foundation of China
Publisher
Wiley
Subject
Applied Mathematics,Algebra and Number Theory
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/nla.2233
Reference36 articles.
1. A Randomized Kaczmarz Algorithm with Exponential Convergence
2. Randomized Methods for Linear Constraints: Convergence Rates and Conditioning
3. Randomized Kaczmarz solver for noisy linear systems
4. Acceleration of randomized Kaczmarz method via the Johnson–Lindenstrauss Lemma
5. Randomized Extended Kaczmarz for Solving Least Squares
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